A Novel Dimension Reduction Procedure for Searching Non-Gaussian Subspaces.
Motoaki KawanabeGilles BlanchardMasashi SugiyamaVladimir G. SpokoinyKlaus-Robert MüllerPublished in: ICA (2006)
Keyphrases
- dimension reduction
- high dimensional data
- principal component analysis
- low dimensional
- high dimensional
- dimensionality reduction
- high dimensionality
- nearest neighbor
- feature space
- linear projection
- manifold learning
- random projections
- feature extraction
- data mining and machine learning
- linear discriminant analysis
- high dimensional problems
- original data
- data points
- lower dimensional
- data sets
- independent component analysis
- partial least squares
- feature subspace
- high dimensional data analysis
- cluster analysis
- subspace clustering
- variable selection
- subspace learning
- singular value decomposition
- discriminative information
- dimension reduction methods
- factor analysis
- data analysis
- training data
- image processing
- training samples
- unsupervised learning
- qr decomposition